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Making sense of economic omens

There is a wealth of data out there. FDs must act as a filter for information that is relevant to the organisation’s future, writes Richard Crump

“THE VALUE OF ECONOMICS should not be gauged by how well economists can forecast the future.” These words, spoken by David Miles, external member of the Bank of England’s Monetary Policy Committee, at a recent lecture exhibit the self-deprecation common in economists. But, more importantly, they also reveal a dilemma for finance directors.

Economics form the cornerstone of company forecasts, annual budgets and company strategy. GDP growth, interest rates, currency fluctuations, employment statistics and inflation all serve to underpin predictions of customer behaviour, the financial health of supply chains, and they will invariably affect business approaches to cost control and financial risk management in the form of hedging activities.

Miles went on to use an analogy of modern medicine as a reason why economics should not be judged by the yardstick of accuracy alone.

“We believe doctors are worth listening to if we have a broken leg or have a brain tumour even though they may not have been able to predict that you would be in that unfortunate position,” he told delegates at the RBS Scottish Economic Society Annual Lecture.

George Buckley, UK chief economist at Deutsche Bank, agrees that the quality of an economist’s forecast is not the best criterion by which to judge how good the economist is.

“A good economist will tell you more about where we are at, what current conjecture is, and what political and economic policies are needed,” Buckley says.

Instant snapshots

Likewise, finance directors should also be judged not only on their ability to provide an instant snapshot of the financial health of the business, but also on what strategies they suggest that the business should adopt in order to drive growth and improve performance. Unlike in the case of economists, the accuracy of their forecasts is everything.

The tools at an FD’s disposal have become more sophisticated – business analytics and enterprise management have come to the fore and rolling forecasts are gradually superceding annual budgets as the best way to drive the business forwards.

Yet most of these tools are focused on company-specific data. How much are customers spending; what are they buying, how much stock is on hand; and the like. Before getting down to the nitty-gritty, the finance director’s first port of call should be the macro-economic conditions that represent the environment in which the business will have to operate.

“Our current view is that we are going through a sequence of events that will continue to push up and down. You are not going to get a nice, freely flowing economy,” Buckley says.

“Shorter business cycles are taking place where central banks are on the limit of what they can do. We will see more cycles and shorter cycles.”

But what data sets matter most, and with so many conflicting opinions, approaches and conclusions, which set of numbers should be most trusted?

Drawing conclusions

In today’s environment, drawing a consistent conclusion is more difficult than it normally is. The information out there is hardly consistent itself. And people rarely seem to agree on whether the information is credible, even when produced by sources that have previously been seen as credible.

Take the Office for National Statistics (ONS) as a case in point. In April, the ONS produced figures that showed the UK economy had returned to recession in the first quarter of the year. According to the ONS, the economy had shrunk by 0.2% in the first three months of the year, a turn of events that came on the back of the 0.3% decline at the end of last year. A 3% decline in the construction sector was cited as the reason behind the contraction.

It was not long before various economic commentators were lining up to heap scorn on the figures.

“The initial reaction to these figures must be one of disbelief,” Andrew Goodwin, senior economic advisor to Ernst & Young’s ITEM Club, said at the time. “The construction figures are an obvious source of bewilderment, but the services data also looks highly questionable given what we already knew about the early part of the quarter.”

In the second quarter, the ONS reported that GDP fell by 0.7% – the third successive quarter of negative growth – though this number was later revised down to 0.5%.

According to Dennis Turner, former chief economist at HSBC and a regular columnist writing in Financial Director, the GDP figure was “clearly at odds with other numbers, some produced by the ONS itself”.

“In the three months from March to May, employment rose by 181,000 and unemployment fell by 65,000,” Turner wrote in a column recently.

“Since the double dip began, the economy has created a quarter of a million new jobs, more than in the boom years of 2002, 2003 and 2006, and the rise in the hours worked is greater than in the 1992-2008 period.”

And while Buckley doesn’t treat the ONS with the same level of suspicion as some, he does think that there are better sources to which FDs should look for a picture of economic performance. “The PMI surveys are terrific,” he says.

The Purchasing Managers’ Index is a composite index designed to measure changes in prevailing business conditions. It polls businesses that represent the make-up of the respective sector – construction, manufacturing, services – to show financial activity reflecting purchasing managers’ acquisition of goods and services.

“They publish globally, at the same time. On top of that, they reliably track what is happening to growth. The PMI is a good, reliable source,” Buckley says.

Performance drivers

GDP figures naturally matter to all finance directors, but they are more prescient to some FDs than to others. David Jones, a director in PwC’s enterprise performance management team, says retailers should take particular note. –

“Total volume of retail sales is very closely related to economic growth,” explains Jones. “The issue becomes about how you can predict what your market share will be. It will become a driver of financial performance.

“The trick is to have a model for economic growth that can be flexible and to do scenario planning around it.”

Employment data will be more important to consumer-facing businesses, while inflation is particularly relevant to public service providers where price increases are directly linked to inflation – and, in turn, commodity prices are likely to affect producers of raw materials, explains Buckley.

“Don’t try to predict in any one month what upstream prices will do. Work out the underlying things they do, and how a rise in commodity costs affects the overall price,” Buckley says.

Economic mess

Business days graphThe annual budgeting process will continue to be a cornerstone of the process of turning relevant data into good business management.

But how much use is it in today’s economic mess, given that it consumes considerable resources and struggles to keep pace with the fluctuations that are now the norm?

According to Jones at PwC, the annual budget is not of great value “in terms of driving the business forwards” – partly because of the length of time it takes to produce that budget. At 120 days for budgets and 19 days for forecasts, typical cycle times are too long for them to have much of an impact.

“It is of value if you want to manage costs tightly at a cost centre management level. The annual budget is a blunt instrument. In terms of driving business, the traditional budget is pretty useless,” explains Jones.

“When the economy is a growth driver, it works, but in a more volatile time the budget is the wrong speed to predict what levers to pull.”

Jones, who contributed to PwC’s recent finance function benchmarking survey, Putting your business on the front foot, explains a typical example is that of a particular retail business – for this company, meeting the annual budget was always the main goal.

“Six months into the year, they found that their economic growth assumptions were overly optimistic and that the budget targets were unbelievable. The many hundreds of spreadsheets used to prepare the budget only made it harder to adjust and respond accordingly to the shift,” Jones wrote in the report.

In another example, Jones cites a manufacturer’s sales and marketing team, which under-estimated sales volumes and repeatedly misjudged the forecast on product mix.

In turn, the production team was working on meeting volume budgets, though it had very little confidence in the forecasts produced by the sales and marketing teams.

“The finance team was constantly being asked to close the gaps between marketing and production, but were themselves hampered by standalone systems and a lack of standardisation and integration,” wrote Jones.

Jones says that smart companies are moving towards a rolling forecast model and are now using integrated planning as well as forecasting techniques that are grounded in the information that actually drives the business.

These companies can turn their budgets around faster than those that don’t use this kind of forecasting – top-performing teams take seven days to produce their forecasts, which compares to the 19 days a typical function takes.

Meanwhile, the high-performing teams are also able to produce a far more accurate picture of a company’s expected performance against which actuarial results can be judged.

Filtering out the chaff

Budgeting graphThe trick is also to spend time focusing on management information that is genuinely useful and to cut back on wasted effort. It is the finance director’s job to filter the pertinent information from the chaff.

Nearly half of the participants in PwC’s survey carry out regular reviews with the rest of the business.

As a consequence of this, they only tend to generate about a third of the standard reports produced by those that don’t, while leading finance teams spend 17% less time on data gathering and 25% more time on analysis than on typical functions.

“You have to go to a sensible time horizon and get the right level of detail. It is easy to fall into the trap of burdening the forecasting process with excessive detail that can reduce flexibility,” says Jones.

An increasing number of finance teams are also using integrated planning tools such as SAP BPC or Oracle/Hyperion Planning to streamline the financial planning process and deliver driver-based budgets. But technology is no answer on its own. The data must be there to support it.

According to PwC, 50% of survey participants have a data warehouse in place but only 11% have applied a standard taxonomy required for comparability across the business.

As Jones’ colleague, Andy McCorkell, director in Saratoga, PwC’s benchmarking practice, says of the process of business forecasting: “Data and its reliability is absolutely the cornerstone of everything.” ?

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